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A multi-objective robust possibilistic programming approach to sustainable public transportation network design

机译:可持续公共交通网络设计的多目标稳健可能性规划方法

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As a critical component of sustainable development, a transportation system should be designed such that it has a positive impact on the economic, environmental, and social sustainability of the served region. In response, this study introduces the concept of passenger dissatisfaction with additional walking and waiting as an indicator of social sustainability and uses the concept while optimizing the transit network for economic, environmental, and social perfectives. Due to a lack of knowledge about the actual value of different passenger dissatisfaction levels and uncertainty in demand, a multi-objective robust possibilistic programming approach (RPP*) is proposed and solved by using an interactive fuzzy programming approach. Different from other robust possibilistic approaches, RPP* optimizes not only the mean of the objective function and chance constraint violations but also the risk value inherited by uncertain parameters through considering the absolute deviation of the objective function. Both the advantage of RPP* versus the deterministic model and its superiority against several robust possibilistic approaches are demonstrated in the numerical studies. Furthermore, the outcomes of the numerical study demonstrate that the transportation network should be designed in a decentralized way as the risk coefficients, i.e., risk-taking attitude, increase. (C) 2020 Elsevier B.V. All rights reserved.
机译:作为可持续发展的关键组成部分,应设计运输系统,使其对服务地区的经济,环境和社会可持续性产生积极影响。作为回应,本研究介绍了乘客不满的概念,并等待社会可持续性的指标,并使用该概念,同时优化经济,环境和社会完善的过境网络。由于对不同乘客不满水平的实际价值和需求不确定性的知识,通过使用交互式模糊编程方法提出和解决了多目标稳健的可能性编程方法(RPP *)。不同于其他强大的可能性方法,RPP *不仅优化了客观函数和机会约束违规的平均值,而且通过考虑目标函数的绝对偏差来优化违规的风险值。在数值研究中,证明了RPP *与确定性模型的优点及其对多种强大可能方法的优越性。此外,数值研究的结果表明,运输网络应以分散的方式设计为风险系数,即风险态度,增加。 (c)2020 Elsevier B.V.保留所有权利。

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